3 Day Trend and Hull Moving Average

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I have been working on a new algorithm for the better sense of the word, I have been playing with some ideas and here is what I have come up with. It's come up with some profitable results so far so I wanted to get your thoughts.

• Take the price for the last 10 days and calculate the Hull Moving Average. The benefit of the Hull moving average is that it cuts out a lot of noise.
• Take the last 3 days close price and check that if it has been all up or all down.
• If the the current price is above the HMA then buy and if it's not sell (All days up) the idea being that it's breaking to the upside or trend reversal if not.
• If the the current price is above the HMA then buy and if it's not sell (All days down)

I currently have the take profit (limit) set at 2% of the current price, I can't figure out a better way of deciding where to set the take profit (in pips)? Anyone got any good Python functions or modules that would let me work that out?

I have a fully working Python algorithm that works with the IG Index API trading on UK stocks if anyone is interested?

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Hi,

This sounds pretty interesting. What are you applying it to? Individual stocks?  Just curious to know,.
I have a couple of ideas, but first, I wonder if there is a typo there, because on your second main bullet, you address "if the current price is above the HMA and if it's not sell" which reads exactly the same as the first bullet, except that you then have (all days up) in one and (all days down) in the other. I don't quite follow. Should one of those sells say buy?

My suggestion for where to set stops would be to link it to some measure of ATR (average true range), perhaps setting this to a 10-day ATR, since the data you're using reaches back as far as 10 days also. This will give a time-varying sense of how much potential the price has (based on the very recent past) to move a given amount. Setting a purely numerical absolute level such as 2% could have wildly different propensities to cut your losses early in different market conditions.

However, it doesn't usually doesn't pay to restrict your upside when trading trends / momentum. Rather than a mechanically derived take-profit level decided at the outset, you might want to keep a trade running if it's still making money which means that the underlying trend is still going, until there is some sign of the trend starting to weaken. You'll never get the full benefit of trend based trading if you reduce the opportunity for your winning trades to become big winners. This is easy enough to build into the rule.

You could have several things that ultimately close your trade and just one of them coming true could be enough to trigger closure. One of them could be in relation to passing below a particular moving average (a shorter one than 10 days, in order to be responsive to deterioration in the trend); another could relate to consecutive days move in the underlying price - in other words some adjusted version of the conditions you used to enter the trade in the first place.

Or you could measure drawdown from the highest point the P&L of the position reached so far. Let's say the trade reached a peak P&L of 10% and then began to drift, and rather than waiting for it to turn upwards again you could ask: (a) have at least 3 days passed without the trade making a new high? (b) has the P&L declined by at least 3% from its high? (this is somewhat similar in nature to having a moving stop loss which you have shifted upwards each period that the trade has gained), and if at least one of these questions is answered YES then close.

There are so many methods but the key is whether a thorough backtest (including out of sample performance) works in a consistent enough way. Also beware of the fact that with many asset price series there's an asymmetry between the behaviour of their upside trends and their downside trends.

Hope this helps!

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Thanks for your detailed reply. Yeah so I have updated it a bit this is the table of how I see the trades working. I am applying this to stocks.

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